SOTAVerified

One-Shot Learning

One-shot learning is the task of learning information about object categories from a single training example.

( Image credit: Siamese Neural Networks for One-shot Image Recognition )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 271–280 of 305 papers

TitleStatusHype
Interactive Instance Annotation with Siamese Networks—0
Inverting The Generator Of A Generative Adversarial Network—0
Investigation of using disentangled and interpretable representations with language conditioning for cross-lingual voice conversion—0
KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning—0
Latent Attention For If-Then Program Synthesis—0
Learning feed-forward one-shot learners—0
Learning from limited datasets: Implications for Natural Language Generation and Human-Robot Interaction—0
Learning in Text Streams: Discovery and Disambiguation of Entity and Relation Instances—0
Learning Non-deterministic Representations with Energy-based Ensembles—0
Learning Relational Representations by Analogy using Hierarchical Siamese Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified